docstr: Calculates the element-wise determinant of the log Jacobian
docstr_tok: ["Calculates","the","element-wise","determinant","of","the","log","Jacobian"]
code: def log_abs_det_jacobian(self, x, y):
      """
      Calculates the element-wise determinant of the log Jacobian
      """
  
      M = self.weights() if callable(self.weights) else self.weights
      return self._trace(M)
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  from torch.distributions import Transform, constraints
  from pyro.nn import DenseNN
  from ..conditional import ConditionalTransformModule
  from ..torch_transform import TransformModule
  from ..util import copy_docs_from
label_desc: Use image node_id 6 for calling the ConditionedMatrixExponential obj's underlying member method code with example usage: obj.log_abs_det_jacobian(x, y) and returns: self